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app.py

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+import pickle
+import streamlit as st
+from streamlit_option_menu import option_menu
+
+#loading the saved data
+
+heart_disease_model = pickle.load(open("E:\jupyter notebook\heart disease prediction\heart_disease_model.sav",'rb'))
+
+st.title('Heart Disease Prediction using ML')
+
+col1, col2, col3 = st.columns(3)
+
+with col1:
+    age = st.text_input('Age')
+
+with col2:
+    sex = st.text_input('Sex')
+
+with col3:
+    cp = st.text_input('Chest Pain types')
+
+with col1:
+    trestbps = st.text_input('Resting Blood Pressure')
+
+with col2:
+    chol = st.text_input('Serum Cholestoral in mg/dl')
+
+with col3:
+    fbs = st.text_input('Fasting Blood Sugar > 120 mg/dl')
+
+with col1:
+    restecg = st.text_input('Resting Electrocardiographic results')
+
+with col2:
+    thalach = st.text_input('Maximum Heart Rate achieved')
+
+with col3:
+    exang = st.text_input('Exercise Induced Angina')
+
+with col1:
+    oldpeak = st.text_input('ST depression induced by exercise')
+
+with col2:
+    slope = st.text_input('Slope of the peak exercise ST segment')
+
+with col3:
+    ca = st.text_input('Major vessels colored by flourosopy')
+
+with col1:
+    thal = st.text_input('thal: 0 = normal; 1 = fixed defect; 2 = reversable defect')
+
+    # code for Prediction
+    heart_diagnosis = ''
+
+    # creating a button for Prediction
+
+    if st.button('Heart Disease Test Result'):
+        heart_prediction = heart_disease_model.predict([[
+            'age', 'sex',' cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal']])
+        if (heart_prediction[0] == 1):
+            heart_diagnosis = 'The person is having heart disease'
+        else:
+            heart_diagnosis = 'The person does not have any heart disease'
+
+    st.success(heart_diagnosis)

heart_disease_data.csv

@@ -0,0 +1,304 @@
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